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Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Questions
- Salesforce Consultant Certifications
- Salesforce CRM Analytics and Einstein Discovery Consultant Certifications
- Topic 1: Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.
- Topic 2: Security: Consultants stepping into this section will showcase their prowess in implementing necessary security settings. It covers critical aspects such as suitable dataset security settings, and the ability to implement app sharing.
- Topic 3: Admin/Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync/dataflows/recipe limits.
- Topic 4: Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.
- Topic 5: Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.
- Topic 6: Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.
Free Salesforce Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Actual Questions
Note: Premium Questions for Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) were last updated On Aug. 14, 2026 (see below)
Cloud Kicks needs a CRM Analytics consultant to install the Appointment Analytics App. After installation, they realize the wrong field was picked and the app did not have access to a newly created field that should be used instead of the old one.
What is the first step the consultant should take to prevent erroneous dataset/dashboard creation?
If the wrong field is selected in the initial setup of an app or dataset, it is important to stop any data processing activities (like recipe executions) to prevent erroneous data from being loaded into datasets and dashboards. In this case, stopping the recipe from running in Data Manager is the correct first step. Once the recipe is stopped, the consultant can update the field selection or make other necessary corrections before restarting the process.
A company wants to create a timeline chart to visualize the evolution of its Closed Won opportunities.
What are the required parameters to build a lens that displays output similar to the image shown?
To create a timeline chart similar to the one shown, the following parameters are typically required:
1 Measure: This could be the count of Closed Won opportunities or any other relevant metric that needs to be tracked over time.
1 Grouping by a Date Field: This is essential to plot the timeline effectively. The date field would typically be the close date of the opportunities.
Additional Groupings: Depending on the complexity and the detail needed, additional groupings can be added. For example, grouping by region or product line can provide more insights into the timeline. If trellis is used, it allows for the creation of multiple smaller charts within the main chart, each representing a slice of data based on the additional groupings.
This setup helps visualize the evolution of Closed Won opportunities over time, making it easy to spot trends, seasonal patterns, or other relevant insights.
Universal Containers builds a new sales dashboard and wants to make sure account managers can access the dashboard while traveling.
What should the consultant consider doing in this process?
Universal Containers has a well-defined role hierarchy in Salesforce where everyone is assigned to an appropriate node. The accounts within their instance are categorized by their demography.
An individual sales rep should be able to view all accounts that they own. In addition, sales reps should be able to see any accounts where the value of the account demography matches the demography defined on their user record. A user could have more than one demography defined on their user record.
To meet this requirement, the CRM Analytics consultant has set up a security predicate of the existing 'Account' dataset as follows:
This, however, does not seem to be working as expected.
What is causing the issue?
The issue with the security predicate not functioning as expected likely stems from a permissions issue related to the custom field Demographic__c on the User object. Here's a detailed explanation:
Field-Level Security: If the sales reps do not have access to the Demographic__c field, the security predicate which references this field cannot execute properly as the system cannot evaluate the predicate without accessing the field.
Permission Settings: Ensuring that the sales reps have the necessary permissions to view and use the Demographic__c field is crucial for the security predicate to function correctly.
Data Visibility: The security model in CRM Analytics relies heavily on the underlying data permissions in Salesforce. If these permissions are not correctly configured, the expected data visibility through CRM Analytics will not be achieved.
Which capability can a consultant use if ''Deploy without connecting to a Salesforce Object'' is selected while deploying the model?
When deploying a model with the option 'Deploy without connecting to a Salesforce Object', the suitable capabilities include:
Use of Predict Function in Salesforce Flows: This capability allows the deployed model to be used within Salesforce Flow as a predictive tool, enabling automation flows to include predictions without directly writing back to Salesforce objects.
Flexibility in Application: This method provides flexibility in how predictions are utilized across various Salesforce processes and workflows, without the need for direct data manipulation within Salesforce objects.
Enhanced Workflow Integration: By integrating predictive insights directly into flows, organizations can automate decision-making processes, enhance user interactions, and streamline operations based on predictive outcomes.
This setup aligns with Salesforce's best practices for leveraging CRM Analytics to enhance operational efficiency and decision accuracy across different business functions.
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